SAP C_SACS_2321 SAP Certified Application Associate - SAP Analytics Cloud Story Design Exam Practice Test

A dataset is a type of data source that allows you to import data from files, such as Excel or CSV files. You can use datasets to create stories or blend data with models. However, datasets have some limitations, such as:

• They cannot be scheduled. You have to manually refresh the data in a dataset.
• They do not support column-based or property security. You cannot restrict access to certain columns or properties in a dataset.
• They do not support transformations. You cannot apply any transformations to the data in a dataset.
• They can overwrite imported data. You can choose to append or replace the data in a dataset when you import a new file.

Therefore, the correct answer is They cannot be scheduled and They do not support column-based or property security, as they are the limitations of datasets.

A section is a way of organizing a story into different parts based on a dimension. A section creates a separate page for each member of the dimension, and displays the same widgets on each page with the data filtered by the section dimension1. For example, if you create a section based on the Country dimension, you will have a page for each country in your data, and the charts and tables on each page will show only the data for that country.

The other options are not correct because:

• Value Driver Tree: This is a widget that allows you to create a graphical representation of how different drivers affect a key performance indicator (KPI). You can use this widget to perform simulations and what-if scenarios on your data2. However, this widget does not create a chart for each member of a dimension.
• In-Cell Charts: These are mini charts that are displayed within table cells to show the relative values of measures. You can use this feature to enhance the readability and analysis of your data3. However, this feature does not create a chart for each member of a dimension.
• Trellis: This is a feature that allows you to split a chart into multiple smaller charts based on one or more dimensions. You can use this feature to compare and contrast different segments of your data4. However, this feature does not create a separate page for each member of a dimension.

References:

1: Creating Sections - SAP Learning 2: Using Value Driver Trees - SAP Learning 3: Using In-Cell Charts - SAP Learning 4: Using Trellis Charts - SAP Learning

To apply the formatting of the year 2024 to the years 2025 and 2026, you need to use the level option Self and Descendants in the styling rules. This option applies the formatting to the selected member and all its lower-level members in the hierarchy1. In this case, the selected member is the year 2024, and its lower-level members are the months, quarters, and half years that belong to 2024. The formatting will also be applied to the years 2025 and 2026, and their lower-level members, because they are at the same level as 2024 in the hierarchy.

The other level options are:

• Self: This option applies the formatting only to the selected member, not to any other members in the hierarchy1. In this case, the selected member is the year 2024, and the formatting will not be applied to any other years or lower-level members.
• Self and Siblings: This option applies the formatting to the selected member and all its siblings, which are members at the same level in the hierarchy1. In this case, the selected member is the year 2024, and its siblings are the years 2025 and 2026. The formatting will be applied to these three years, but not to their lower-level members.
• Self and Children: This option applies the formatting to the selected member and its immediate children, which are members one level below in the hierarchy1. In this case, the selected member is the year 2024, and its immediate children arethe quarters and half years that belong to 2024. The formatting will be applied to these members, but not to any other years or months.

Data point comments are a feature that allows you to add comments to specific data points in a story. You can use data point comments to provide additional information, context, or feedback on the data. You can also reply to, edit, or delete existing comments. Data point comments are supported for the following models:

• Import models
• Planning models
• Blended models

Data point comments are not supported for live models, such as SAP S/4HANA live model or BPC live model. Therefore, the correct answer is Import planning model and Blended model, as they are the models that support data point comments. 

Data point comments are comments that you can add to a specific value in a table or a comment widget. They are similar to commenting on a single cell in Microsoft Excel. Data point comments are associated with the models, which means that they will appear in any story that uses the same model and has the same value in a table or a comment widget1.

Data point comments can be added to the following models:

• Import planning model: This is a model that you create by importing data from a file or a database. You can use this model for planning scenarios, such as budgeting, forecasting, or what-if analysis. You can enable data point comments forthis model by selecting the Allow Data Point Comments option in the model properties2.
• BPC live model: This is a model that you create by connecting to a SAP Business Planning and Consolidation (BPC) system. You can use this model for real-time planning and analysis with BPC data. You can enable data point comments for this model by selecting the Allow Data Point Comments option in the model properties3.

Data point comments cannot be added to the following models:

• SAP S/4HANA live model: This is a model that you create by connecting to a SAP S/4HANA system. You can use this model for real-time analysis with SAP S/4HANA data. However, this model does not support data point comments, because it is read-only and does not allow any changes to the data4.
• Blended model: This is a model that you create by blending data from two or more models. You can use this model for combining and analyzing data from different sources. However, this model does not support data point comments, because it is derived from other models and does not have its own data.

References:

1: Using Data Point Comments - SAP Learning 2: Creating an Import Planning Model - SAP Learning 3: Creating a BPC Live Model - SAP Learning 4: Creating an SAP S/4HANA Live Model - SAP Learning : [Blending Data from Multiple Models - SAP Learning]

These are two of the options that you can use for data wrangling when you import a file for a story in SAP Analytics Cloud, according to the SAP Help Portal1. Data wrangling is the process of cleaning, structuring, and enriching raw data into a desired format for better decision making in less time2.

The custom expression editor is a tool that allows you to create or edit formulas and expressions for your data columns3. You can access the custom expression editor by clicking on the formula icon in the builder panel or by double-clicking on a column header in the data view3. The custom expression editor provides a list of functions and operators that you can use to manipulate your data, such as arithmetic, logical, string, date, and aggregation functions3. You can also use the custom expression editor to create calculated columns or measure-based dimensions from your existing columns3.

The transform bar is a tool that allows you to apply various transformations to your data columns, such as renaming, reordering, grouping, splitting, merging, or deleting columns4. You can access the transform bar by clicking on the transform icon in the builder panel or by right-clicking on a column header in the data view4. The transform bar provides a list of actions that you can use to modify your data structure, such as move left, move right, group by, split by delimiter, merge columns, or delete column4. You can also use the transform bar to change the data type or format of your columns, such as text, number, date, currency, or percentage4.

When break grouping is enabled, the sort is applied to the inner dimension of the chart or table, according to the SAP Analytics Cloud Help1. Break grouping is a feature that allows you to sort data points in a chart or table by breaking the grouping of the dimensions in the category axis2. For example, if you have a chart with two dimensions in the category axis, such as Country and Product, and you enable break grouping, you can sort the data points by Product instead of Country2. This can help you compare the performance of different products across countries. You can also choose to sort by measure values or custom order2.

The other options are not correct. Option A. The outer dimension is the dimension that is not affected by the break grouping feature. Option C. The vertical dimension and option D. The horizontal dimension are not relevant terms for break grouping, as it depends on how you arrange the dimensions in the category axis.

1: Apply Smart Grouping to Charts in Analytic Applications | SAP Help Portal 2: Sort Data Points in Charts and Tables | SAP Help Portal

Chart scaling is a feature that ensures that you have a meaningful display of values across multiple charts in a story. By default, charts are not scaled, which can lead to incorrect data analysis, particularly if users are not paying attention to the actual values displayed in the chart1.

Chart scaling is applied to the following:

• Specific page: Chart scaling is applied to all of the charts on a page, but the scaling may be different for the same measure on different pages, because the scaling factor is calculated separately for each page1.
• Specific measure: Chart scaling is applied to a specific measure in a chart, and it affects all the charts that contain that measure on the same page. You can exclude charts from the scaling by selecting the chart and choosing Exclude from Scaling in the context menu1.

Chart scaling is not applied to the following:

• All measures: Chart scaling is not applied to all the measures in a story, only to the ones that are selected for scaling. You can select which measures to scale by choosing Scale Measures in the context menu of any chart on a page1.
• All pages: Chart scaling is not applied to all the pages in a story, only to the ones that have scaling enabled. You can enable or disable scaling for a page by choosing Enable Scaling or Disable Scaling in the context menu of any chart on a page1.

An input control is a type of filter that allows you to dynamically change the values of dimensions or measures in your story or application. You can use an input control to filter dimension or measure values and select dimension or measure values for your widgets, such as charts, tables, or geo maps1. For example, you can create an input control that lets you choose which product category or year to display in your chart2.

You cannot use an input control to define a prompt or explore data relationships. A prompt is a filter that is applied to a model before the data is loaded into a story or an application. Prompts allow you to select the data that you want to see in your story or application. You can create prompts in the modeler, not in the story or application3. To explore data relationships, you can use the Smart Discovery feature, which allows you to automatically generate insights and visualizations based on your data. You can access Smart Discovery from the context menu of a chart or table widget4.

 Explanation: According to the SAP Help Portal1, you can configure different add-ons for a chart to enhance its appearance and functionality. Some of the add-ons that are available are:

• Variance: This add-on allows you to compare two measures and show the difference and percentage difference between them. You can also choose to display the variance as a bar, line, or area chart on top of the original chart2.
• Scaling: This add-on allows you to adjust the scale of the chart axes to better fit the data range. You can choose to use a linear, logarithmic, or percentage scale for the axes3.
• Linked Analysis: This add-on allows you to link multiple charts or tables that share the same data source. When you select a data point in one chart or table, the other linked charts or tables will filter accordingly4.
• In-Cell Charts: This add-on allows you to display mini charts within the cells of a table. You can choose from different types of in-cell charts, such as bullet, bar, or sparkline charts5.

Therefore, Variance and In-Cell Charts are add-ons that can be configured for a chart, while Scaling and Linked Analysis are not.

The data source connection that can be used in SAP Analytics Cloud to wrangle data is imported. Imported data sources are data files that are uploaded to SAP Analytics Cloud and stored in its internal database. Users can wrangle imported data sources using the Data Preparation feature, which allows them to transform, enrich, cleanse, and merge data. Live and public data sources cannot be used to wrangle data in SAP Analytics Cloud; live data sources remain in their original systems and public data sources are read-only datasets provided by SAP. Verified References: [SAP Analytics Cloud - Data Preparation]

The Optimized Design Experience is a new design option for creating stories in SAP Analytics Cloud. It offers several usability improvements and performance enhancements compared to the Classic Design Experience. However, it also has some limitations and differences, such as the unavailability of some elements that are present in the Classic Design Experience1.

The following filter options are supported in the Optimized Design Experience:

• Input Control: This option allows you to add interactive filters to a story page that allow the story viewers to filter data, compare figures, and explore relationships directly from the page. You can use the Input Controls tool in the Tools section to select dimensions or measures that you want to use as input controls2.
• Cascading: This option allows you to create a hierarchy of input controls that depend on each other. You can use this option to filter data based on multiple levels of a dimension, such as Country, Region, and City. You can also use this option to filter data based on different dimensions that are related, such as Product Category and Product Name3.
• Section: This option is not a filter option, but a way of organizing a story into different parts based on a dimension. A section creates a separate page for each member of the dimension, and displays the same widgets on each page with the data filtered by the section dimension. Sections are available in both the Optimized and Classic Design Experiences4.

The other options are not supported in the Optimized Design Experience, because:

• Advanced: This option allows you to create complex filters using logical operators, such as AND, OR, and NOT. You can use this option to filter data based on multiple conditions or expressions, such as Revenue > 1000 AND Profit Margin < 10%. Advanced filters are available only in the Classic Design Experience.
• Controls: This option is not a valid filter option in SAP Analytics Cloud. It may refer to input controls, which are supported, or chart controls, which are not supported. Chart controls are buttons that allow you to change the chart type, switch between absolute and relative values, or drill up and down in a hierarchy. Chart controls are available only in the Classic Design Experience.

References:

1: Choosing Between Optimized and Classic Design Modes - SAP Learning 2: Using Input Controls - SAP Learning 3: Creating Cascading Input Controls - SAP Learning 4: CreatingSections - SAP Learning : [Advanced Filters - SAP Learning] : [Chart Controls - SAP Learning]

The valid targets for hyperlinks are external websites, SAP Analytics Cloud stories, and SAP Analytics Cloud story pages. External websites are web pages that are outside of SAP Analytics Cloud, such as SAP Analytics Cloud stories are presentation-style documents that use charts, visualizations, text, images, and pictograms to describe data. SAP Analytics Cloud story pages are individual pages within a story that contain one or more widgets. SAP BusinessObjects Web Intelligence documents and SAP Analysis for Microsoft Office workbooks are not valid targets for hyperlinks; they are different types of documents that are not supported by SAP Analytics Cloud. Verified References: [SAP Analytics Cloud - Hyperlinks]

A page type is a property that determines how the elements on a page are arranged and displayed. There are three page types in SAP Analytics Cloud: Canvas, Grid, and Responsive. The page type that is recommended when designing stories is Responsive, as it offers the following advantages:

• It automatically adjusts the layout and size of the elements to fit different screen sizes and orientations.
• It provides a consistent and optimal viewing experience across different devices, such as desktops, tablets, and mobile phones.
• It supports all types of elements, such as charts, tables, geo maps, images, text, etc.
• It supports advanced features, such as linked analysis, input controls, story filters, etc.

Therefore, the correct answer is Responsive, as it is the recommended page type when designing stories. 

The SAP Digital Boardroom supports engaging with a remote audience through annotations and screen sharing. Annotations allow users to highlight or draw on the screen using different colors and shapes, which can help to emphasize key points or explain complex concepts. Screen sharing allows users to share their screen with other participants who join the digital boardroom session via a web browser, which can help to facilitate collaboration and communication. Data Analyzer and story editing are not features that support engaging with a remote audience; they are features that allow users to analyze data or modify stories in the digital boardroom. Verified References: [SAP Analytics Cloud - Digital Boardroom]

SAP Datasphere is a data source that does not require a model to be created in SAP Analytics Cloud. You can use a SAP Datasphere connection to access or import data directly into your story, with no need for a SAP Analytics Cloud model to be created1

SAP Business Warehouse, SAP S/4HANA, and SAP BusinessObjects Web Intelligence document are data sources that require a model to be created in SAP Analytics Cloud. You cannot access or import data from these sources directly into your story, but you need to create a model in SAP Analytics Cloud using the connections to these sources234

The SAP BW live model is a type of live data connection that allows you to access data from SAP Business Warehouse (BW) systems without importing it into SAP Analytics Cloud. The SAP BW live model supports the following calculation types:

• Aggregation: You can use aggregation functions, such as SUM, COUNT, MIN, MAX, etc., to calculate the values of a measure based on a dimension or a filter.
• Currency conversion: You can use currency conversion to convert the values of a measure from one currency to another based on predefined exchange rates.
• Unit conversion: You can use unit conversion to convert the values of a measure from one unit of measurement to another based on predefined conversion factors.

The SAP BW live model does not support the following calculation types:

• Dimension to measure: You cannot convert a dimension to a measure in a SAP BW live model.
• Date difference: You cannot calculate the difference between two dates in a SAP BW live model.
• Story calculation: You cannot create story calculations in a SAP BW live model.

Therefore, the correct answer is Aggregation, as it is the calculation type that the SAP BW live model supports. Verified References:

• : Create Calculations in Models
• : SAP BW Live Data Connection

In the Optimized Design Experience, Data Analyzer is a new tool that replaces Explorer. Data Analyzer allows you to quickly create ad hoc analysis based on models or datasets. You can use Data Analyzer to explore data, create charts and tables, apply filters and calculations, and save your analysis as stories. Data Analyzer is similar to Explorer, but with some enhancements and new features, such as:

• Support for both models and datasets
• Support for planning models
• Support for story calculations
• Support for linked analysis
• Support for responsive pages

Therefore, the correct answer is Data Analyzer, as it is the tool that replaces Explorer in the Optimized Design Experience

Linked Analysis is a feature that allows you to link multiple widgets in a story based on the same model. You can use Linked Analysis to do the following:

• Filter data in multiple widgets by selecting a data point in one widget. For example, if you select Soft Drinks in a chart, all the other linked widgets will show data for Soft Drinks only.
• Drill down or up in multiple widgets by changing the level of detail in one widget. For example, if you drill down from Product Category to Product Name in a table, all the other linked widgets will show data for Product Name as well.
• Highlight data in multiple widgets by hovering over a data point in one widget. For example, if you hover over Germany in a geo map, all the other linked widgets will highlight the data for Germany.

To use Linked Analysis, you need to have the following:

• Multiple widgets based on the same model. You can link any type of widget, such as charts, tables, geo maps, etc., as long as they are based on the same model.
• A common dimension or measure between the widgets. You can link widgets based on any dimension or measure that they share in common.

You do not need to have the following for Linked Analysis:

• Multiple stories. You can use Linked Analysis within the same story. You cannot link widgets across different stories.
• Multiple data models. You can use Linked Analysis with one model only. You cannot link widgets based on different models.
• Multiple pages. You can use Linked Analysis within the same page. You cannot link widgets across different pages.

Therefore, the correct answer is Multiple widgets, as it is the necessary element for Linked Analysis. Verified References:

• : Link Widgets with Linked Analysis